Towards a Generic Format for Linguistic Data................................................................ 6

Arxiv preprint cs/0610116, 2006

DepAnn is an interactive annotation tool for dependency treebanks, providing both graphical and text-based annotation interfaces. The tool is aimed for semi-automatic creation of treebanks. It aids the manual inspection and correction of automatically created parses, making the annotation process faster and less error-prone. A novel feature of the tool is that it enables the user to view outputs from several parsers as the basis for creating the final tree to be saved to the treebank. DepAnn uses TIGER-XML, an XML-based general encoding format for both, representing the parser outputs and saving the annotated treebank. The tool includes an automatic consistency checker for sentence structures. In addition, the tool enables users to build structures manually, add comments on the annotations, modify the tagsets, and mark sentences for further revision.

Language Resources and Evaluation, 2004

This paper presents the process followed to design and build a graphical and language independent tool, Abar-Hitz, for the creation and management of the Basque Dependency Treebank. Abar-Hitz makes the annotation process faster and avoids possible mistakes linguists can make. It is composed of three areas: the corpus area, the tagging area and the tree visualizer area. Three linguists used Abar-Hitz to tag 25.000 word-forms from the Eus3LB corpus, making clear, as the evaluation results show, its utility.

Proc. of the Fifth Intern. …, 2006

The paper presents the initial release of the Slovene Dependency Treebank, currently containing 2000 sentences or 30.000 words. Our approach to annotation is based on the Prague Dependency Treebank, which serves as an excellent model due to the similarity of the languages, the existence of a detailed annotation guide and an annotation editor. The initial treebank contains a portion of the MULTEXT-East parallel word-level annotated corpus, namely the first part of the Slovene translation of Orwell's "1984". This corpus was first parsed automatically, to arrive at the initial analytic level dependency trees. These were then hand corrected using the tree editor TrEd; simultaneously, the Czech annotation manual was modified for Slovene. The current version is available in XML/TEI, as well as derived formats, and has been used in a comparative evaluation using the MALT parser, and as one of the languages present in the CoNLL-X shared task on dependency parsing. The paper also discusses further work, in the first instance the composition of the corpus to be annotated next.

arXiv (Cornell University), 2020

We present a richly annotated and genre-diversified language resource, the Prague Dependency Treebank-Consolidated 1.0 (PDT-C 1.0), the purpose of which is-as it always been the case for the family of the Prague Dependency Treebanks-to serve both as a training data for various types of NLP tasks as well as for linguistically-oriented research. PDT-C 1.0 contains four different datasets of Czech, uniformly annotated using the standard PDT scheme (albeit not everything is annotated manually, as we describe in detail here). The texts come from different sources: daily newspaper articles, Czech translation of the Wall Street Journal, transcribed dialogs and a small amount of user-generated, short, often non-standard language segments typed into a web translator. Altogether, the treebank contains around 180,000 sentences with their morphological, surface and deep syntactic annotation. The diversity of the texts and annotations should serve well the NLP applications as well as it is an invaluable resource for linguistic research, including comparative studies regarding texts of different genres. The corpus is publicly and freely available.

2000

CELLAR is not a particular annotation schema, but is a system for expressing and building annotation schemas. The paper illustrates how an annotation schema is expressed as an XML document that defines classes of objects, their properties, and the relationships between objects. The schema is then implemented via automatic conversion to a relational database schema and an XML DTD for data import and export. Requirements for Linguistic Data Modeling CELLAR is a data modeling system that was built specifically for the purpose of linguistic annotation. It was designed to model the following five fundamental aspects of the nature of linguistic data: 1. The data in a text unfold sequentially; the data model must therefore be able to represent text in proper sequence. 2. The data are hierarchically structured; the data model must therefore be able to express hierarchical structures of arbitrary depth. 3. The data elements bear information in many simultaneous dimensions; the data model mus...

The Prague Bulletin of Mathematical Linguistics, 2008

is paper compares the two FGD-based annotation scenarios for Czech and for English, with the Czech as the basis. We discuss the secondary predication expressed by infinitive and its functions in Czech and English, respectively. We give a few examples of English constructions that do not have direct counterparts in Czech (e.g., tough movement and causative constructions with make, get, and have), as well as some phenomena central in English but much less employed in Czech (object raising or control in adjectives as nominal predicates), and, last, structures more or less parallel both in their function and distribution, whose respective annotation differs due to significant differences in the respective linguistic traditions (verbs of perception).

… of Workshop on Recent Advances in …, 2004

Among the variety of proposals currently making the dependency perspective on grammar more concrete, there are several treebanks whose annotation exploits some form of Relational Structure that we can consider a generalization of the fundamental idea of dependency at various degrees and with reference to different types of linguistic knowledge. The paper describes the Relational Structure as the common underlying representation of treebanks which is motivated by both theoretical and task-dependent considerations. Then it presents a system for the annotation of the Relational Structure in treebanks, called Augmented Relational Structure, which allows for a systematic annotation of various components of linguistic knowledge crucial in several tasks. Finally, it shows a dependency-based annotation for an Italian treebank, i.e. the Turin University Treebank, that implements the Augmented Relational Structure.

We present a new version of the Croatian Dependency Treebank. It constitutes a slight departure from the previously closely observed Prague Dependency Treebank syntactic layer annotation guidelines as we introduce a new subset of syntactic tags on top of the existing tagset. These new tags are used in explicit annotation of subordinate clauses via subordinate conjunctions. Introducing the new annotation to Croatian Dependency Treebank, we also modify head attachment rules addressing subordinate conjunctions and subordinate clause predicates. In an experiment with data-driven dependency parsing, we show that implementing these new annotation guidelines leeds to a statistically significant improvement in parsing accuracy. We also observe a substantial improvement in inter-annotator agreement, facilitating more consistent annotation in further treebank development.

2013

In this paper, we present the results of the parallel Czech coreference and bridging annotation in the Prague Dependency Treebank 2.0. The annotation is carried out on dependency trees (on the tectogrammatical layer). We describe the inter-annotator agreement measurement, classify and analyse the most common types of annotators’ disagreement. On two selected long texts, we asked the annotators to mark the degree of certainty they have in some most problematic points; we compare the results to the inter-annotator agreement measurement.

The Prague Czech-English Dependency Treebank (PCEDT) is a syntactically annotated Czech-English parallel corpus. The Penn Treebank has been translated to Czech, and its annotation automatically transformed into dependency annotation scheme. The dependency annotation of Czech is done from plain text by automatic procedures. A small subset of corresponding Czech and English sentences has been annotated by humans. First experiments in Czech-English machine translation using these data have already been carried out. The resources have been created at Charles University in Prague and released by Linguistic Data Consortium in 2004.